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Yosef Ashibani, Dylan Kauling and Qusay H. Mahmoud
There has been a rapid increase in the number of Internet of Things (IoT) devices in the last few years, providing a wide range of services such as camera feeds, light controls, and door locks for remote access. Access to IoT devices, whether within the ...
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Fatemeh Ghanaati, Gholamhossein Ekbatanifard and Kamrad Khoshhal Roudposhti
In recent years, next location prediction has been of paramount importance for a wide range of location-based social network (LBSN) services. The influence of geographical and temporal contextual information (GTCI) is crucial for analyzing individual beh...
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Gemma Di Federico and Andrea Burattin
Process mining analyzes events that are logged during the execution of a process, with the aim of gathering useful information and knowledge. Process discovery algorithms derive process models that represent these processes. The level of abstraction at w...
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Mohammed N. AlJarrah, Qussai M. Yaseen and Ahmad M. Mustafa
The Android platform has become the most popular smartphone operating system, which makes it a target for malicious mobile apps. This paper proposes a machine learning-based approach for Android malware detection based on application features. Unlike man...
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Dongyue Guo, Zichen Zhang, Peng Fan, Jianwei Zhang and Bo Yang
Recognizing isolated digits of the flight callsign is an important and challenging task for automatic speech recognition (ASR) in air traffic control (ATC). Fortunately, the flight callsign is a kind of prior ATC knowledge and is available from dynamic c...
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Stefan F. Beck, Jimmy Abualdenien, Ihab H. Hijazi, André Borrmann and Thomas H. Kolbe
Information models from the domains Building Information Modeling (BIM) and Urban Information Modeling (UIM) are generally considered as information silos due to their heterogeneous character. These information silos can be bridged through linking where ...
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Alexandru Doroban?iu and Remus Brad
With the increased use of image acquisition devices, including cameras and medical imaging instruments, the amount of information ready for long term storage is also growing. In this paper we give a detailed description of the state-of-the-art lossless c...
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Camila Vaccari Sundermann, Marcos Aurélio Domingues, Roberta Akemi Sinoara, Ricardo Marcondes Marcacini and Solange Oliveira Rezende
Recommender systems help users by recommending items, such as products and services, that can be of interest to these users. Context-aware recommender systems have been widely investigated in both academia and industry because they can make recommendatio...
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Phivos Mylonas
After many decades of flourishing computer science it is now rather evident that in a world dominated by different kinds of digital information, both applications and people are forced to seek new, innovative structures and forms of data management and o...
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Pág. 25 - 53
Decomposition regression incorporating contextual factors seems to be a natural choice for exploiting both reliability of statistical forecasting and flexibility of judgmental forecasting using contextual information. However, such a regression model suf...
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Guy Gable
This paper presents the contextual framework for a multi-method, multi-study of the State of the Information Systems Academic Discipline in Australia, and relates the genesis of the Australian study as preliminary to a larger Pacific-Asia study. Analysis...
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Hao Wang, Miao Li, Jianyong Duan, Li He and Qing Zhang
Previous work has demonstrated that end-to-end neural sequence models work well for document-level event role filler extraction. However, the end-to-end neural network model suffers from the problem of not being able to utilize global information, result...
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Guy Austern, Tanya Bloch and Yael Abulafia
The application of machine learning (ML) for the automatic classification of building elements is a powerful technique for ensuring information integrity in building information models (BIMs). Previous work has demonstrated the favorable performance of s...
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Yan Zhou, Kaixuan Zhou and Shuaixian Chen
The rapid development of big data technology and mobile intelligent devices has led to the development of location-based social networks (LBSNs). To understand users? behavioral patterns and improve the accuracy of location-based services, point-of-inter...
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Adebola Omolaja, Abayomi Otebolaku and Ali Alfoudi
Smart devices, such as smartphones, smartwatches, etc., are examples of promising platforms for automatic recognition of human activities. However, it is difficult to accurately monitor complex human activities on these platforms due to interclass patter...
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Matthias Steidel, Jan Mentjes and Axel Hahn
Research in the field of maritime anomaly detection and vessel behavior prediction primarily focuses on developing methods for extracting typical vessel movement patterns from historical traffic data. However, contextual information is currently not cons...
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Shuiyan Li, Rongzhi Qi and Shengnan Zhang
Compared with English named entity recognition (NER), Chinese NER faces significant challenges due to the flexible, non-standard word formation and vague word boundaries, which cause a lot of boundary ambiguity and reduce the accuracy of entity identific...
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Alejandro Rivero-Rodriguez,Paolo Pileggi,Ossi Antero Nykänen
Pág. pp. 25 - 32
Mobile applications often adapt their behavior according to user context, however, they are often limited to consider few sources of contextual information, such as user position or language. This article reviews existing work in context-aware systems (C...
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Islam T. Almalkawi,Jafar Raed,Ayoub Alsarhan,Alaa Abdallah,Emad Abdallah
Pág. pp. 43 - 69
Even though many security schemes proposed for wireless sensor networks protect transmitted data content from being revealed to different types of attacks and fulfill most of the desired security requirements, they are not addressing concealing the priva...
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